• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.2
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• pp.473-480
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• 2013

In this paper, location recognition algorithm is developed to improve the accuracy using improve Trilateration. The location recognition algorithm is first calculate the location refer to the measured signal power. Error can be occurred when measure distance with arranged node in specific location. If the distance data is received from node (receiver, coordinator), Node selected for location calculation is defined through section. If the distance data is received from node (receiver, coordinator), Node selected for location calculation is defined through section. Second, we apply algorithm of section filtering. If there are 4 sections in node, we consider 1 section to 6 location recognition coordinates. A special characteristic drawback of RF is that the actual distance is actually farther than the calculated received distance data. This is error is incurred when the signal strength increases. We reduce the location recognition error by applying an improved algorithm as secondary after filtering primary through section filtering.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.527-528
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• 2022

It is not easy to identify the location of mobile terminals based on drones in the mountainous area, the densely populated urban area, or the space where mobile terminals can easily move by using equipments or modules that can recognize the location of sensors or mobile terminals with LBS (Location-Based Service). However, although the performance of GPS has developed due to the development of technology, it is still widely used in position recognition systems using GPS modules in the sea and onshore, and there is much room for more utilization. Currently, most of the existing sensor networks need to send at least three location information messages to mobile terminals with location information that a plurality of mobile base stations depend on GPS. However, location recognition of mobile repeaters that maintain a certain movement speed using acceleration sensors is necessary for efficient communication network connection.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.3
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• pp.215-221
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• 2010

This paper introduces development of location estimation and navigation system of mobile robots using USN and LEGO Mindstorms NXT. Developed system includes location estimation, location and navigation information display and navigation control parts. It used ZigBee based USN which was built with CC2431 chip to locate blind node and implemented fuzzy model to improve ability of calculation of distances from reference nodes and location of mobile robots. This paper proposed combination method of location estimation using USN and encoder which is built in motors of mobile robots. Experimental results showed proposed method is superior to the method which used USN only in location estimation and navigating robots. Developed system can locate current position of mobile robots and monitor information from sensor nodes like temperature, humidity and send control signal to mobile robot to move.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.06a
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• pp.11-12
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• 2008

• Journal of Biomedical Engineering Research
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• v.28 no.4
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• pp.494-502
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• 2007

Ubiquitous location based services (u-LBS) will be interested to an important services. They can easily recognize object position at anytime, anywhere. At present, many researchers are making a study of the position recognition and tracking. This paper consists of postion recognition and user identification system. The position recognition is based on location under services (LBS) using a signal strength map, a database is previously made use of empirical measured received signal strength indicator (RSSI). The user identification system automatically controls instruments which is located in home. Moreover users are able to measures body signal freely. We implemented the multi-hop routing method using the Star-Mesh networks. Also, we use the sensor devices which are satisfied with the IEEE 802.15.4 specification. The used devices are the Nano-24 modules in Octacomm Co. Ltd. A RSSI is very important factor in position recognition analysis. It makes use of the way that decides position recognition and user identification in narrow indoor space. In experiments, we can analyze properties of the RSSI, draw the parameter about position recognition. The experimental result is that RSSI value is attenuated according to increasing distances. It also derives property of the radio frequency (RF) signal. Moreover, we express the monitoring program using the Microsoft C#. Finally, the proposed methods are expected to protect a sudden death and an accident in home.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.11
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• pp.884-890
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• 2018

In this paper, an improved method of estimating static source location is proposed based on the direct position determination(DPD) method, which estimates a source position directly using received signals. When the source position is estimated using the conventional DPD method, the estimation accuracy and error depend on a pair of receivers: a reference receiver and one of the multiple moving receivers. Based on this, the weighting values of the estimating source location were obtained using the covariance matrix for the pair of receivers($S_1$, $S_{2i}$) and applied to the DPD algorithm. Finally, the source position was estimated using the proposed DPD algorithm, and it was verified that the estimation accuracy improved, compared to the conventional DPD algorithm.

• Journal of Korean society of Dental Hygiene
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• v.10 no.4
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• pp.655-661
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• 2010

Objectives : This study is aimed to prevent the damage to the inferior alveolar nerve during the orthognathic surgery. Methods : The control group consist of 50 patients with class I occlusion. The experimental group consist of 50 patients with class III malocclusion. The cepalometric radiography was used to evaluate the position of the mental foramina. Results : In the first, mental foramen position of class III was more inferior 0.85 mm in the distance between base of mandible and mental foramen. But the distance between occlusal plan and mental foramen had not statistically significant. Secondly, mental foramen location of Mandibular Prognathism was more anterior 0.91 mm in the distance between coronal plane of mandible included pogonion point and mental foramen. Also, the distance of occlusal-coronal plane of mandible included central incisor and mental foramen had statistically significant. The mental foramen location of class III was more anterior 4.81 mm than class I patients. Conclusions : The result of this study could help the clinicians to apprehend fundamental data with various facial skeletal types for any related researches about the location of the mental foramina for other purposes.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.846-849
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• 2008

In recent years there has been growing interest in wireless sensor networks (WSNs) for a variety of indoor applications. In this paper, we present the RSSI-based localization in indoor environments. In order to evaluate the relationship between distance and RSSI, the log-normal path loss shadowing model is used. By tagging users with a sensor node and deploying a number of nodes at fixed position in the building, the RSSI can be used to determine the position of tagged user. This system operates by recording and processing signal strength information at the base stations. It combines Euclidean distance technique with signal strength matrix obtained during real-time measurement to determine the location of user. The experimental results presented the ability of this system to estimate user's location with a accuracy.

• Physical Therapy Korea
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• v.13 no.4
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• pp.64-70
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• 2006

The purpose of this study was to determine whether a relationship existed between foot type and the location of plantar callus in healthy subjects. Twenty-five healthy subjects with plantar callus were recruited for this study. Foot deformities were classified according to the operational definitions as 1) a compensated forefoot varus, 2) an uncompensated forefoot varus or forefoot valgus, or 3) a compensated rearfoot varus. The location of plantar callus was divided into two regions. Fourteen of the 19 feet with compensated forefoot varus and six of the 9 feet showed plantar callus at the second, third or fourth metatarsal head. Five of the 6 feet with uncompensated forefoot varus and twenty of the 16 feet with forefoot valgus showed plantar callus at the first or fifth metatarsal head. A significant relationship was found between foot type and location of callus (p<.01). The results support the hypothesis that certain foot types are associated with characteristic patterns of pressure distribution and callus formation. We believe diabetic patients with insensitive feet and with the types of foot deformity should be fit with foot orthoses and footwears that accommodate their respective deformity in a position as near to the subtalar joint as possible with the goal of preventing plantar ulceration.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.2
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• pp.181-188
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• 2013

In this paper, we present a system design for location determination inside the ship. Since the GPS signal can not be received in the interior of the large vessel, we use the vessel wireless AP (Access Point) RSSI (received signal strength indication) to accurately measure the position. We convert the RSSI for the 3 AP's into distance through the Friis formula and get the location through triangulation. The signal strength varies irregularly due to noise making it difficult to obtain the exact location. Thus Kalman filter is used to real-time position correction, that is store in a server database.